ABSTRACT
OBJECTIVES: This study developed an integrated database for 15 regional biobanks that provides large quantities of high-quality bio-data to researchers to be used for the prevention of disease, for the development of personalized medicines, and in genetics studies. METHODS: We collected raw data, managed independently by 15 regional biobanks, for database modeling and analyzed and defined the metadata of the items. We also built a three-step (high, middle, and low) classification system for classifying the item concepts based on the metadata. To generate clear meanings of the items, clinical items were defined using the Systematized Nomenclature of Medicine Clinical Terms, and specimen items were defined using the Logical Observation Identifiers Names and Codes. To optimize database performance, we set up a multi-column index based on the classification system and the international standard code. RESULTS: As a result of subdividing 7,197,252 raw data items collected, we refined the metadata into 1,796 clinical items and 1,792 specimen items. The classification system consists of 15 high, 163 middle, and 3,588 low class items. International standard codes were linked to 69.9% of the clinical items and 71.7% of the specimen items. The database consists of 18 tables based on a table from MySQL Server 5.6. As a result of the performance evaluation, the multi-column index shortened query time by as much as nine times. CONCLUSIONS: The database developed was based on an international standard terminology system, providing an infrastructure that can integrate the 7,197,252 raw data items managed by the 15 regional biobanks. In particular, it resolved the inevitable interoperability issues in the exchange of information among the biobanks, and provided a solution to the synonym problem, which arises when the same concept is expressed in a variety of ways.
Subject(s)
Biological Specimen Banks , Classification , Data Collection , Genetics , Korea , Logical Observation Identifiers Names and Codes , Precision Medicine , Systematized Nomenclature of MedicineABSTRACT
OBJECTIVES: This study developed an integrated database for 15 regional biobanks that provides large quantities of high-quality bio-data to researchers to be used for the prevention of disease, for the development of personalized medicines, and in genetics studies. METHODS: We collected raw data, managed independently by 15 regional biobanks, for database modeling and analyzed and defined the metadata of the items. We also built a three-step (high, middle, and low) classification system for classifying the item concepts based on the metadata. To generate clear meanings of the items, clinical items were defined using the Systematized Nomenclature of Medicine Clinical Terms, and specimen items were defined using the Logical Observation Identifiers Names and Codes. To optimize database performance, we set up a multi-column index based on the classification system and the international standard code. RESULTS: As a result of subdividing 7,197,252 raw data items collected, we refined the metadata into 1,796 clinical items and 1,792 specimen items. The classification system consists of 15 high, 163 middle, and 3,588 low class items. International standard codes were linked to 69.9% of the clinical items and 71.7% of the specimen items. The database consists of 18 tables based on a table from MySQL Server 5.6. As a result of the performance evaluation, the multi-column index shortened query time by as much as nine times. CONCLUSIONS: The database developed was based on an international standard terminology system, providing an infrastructure that can integrate the 7,197,252 raw data items managed by the 15 regional biobanks. In particular, it resolved the inevitable interoperability issues in the exchange of information among the biobanks, and provided a solution to the synonym problem, which arises when the same concept is expressed in a variety of ways.
Subject(s)
Biological Specimen Banks , Classification , Data Collection , Genetics , Korea , Logical Observation Identifiers Names and Codes , Precision Medicine , Systematized Nomenclature of MedicineABSTRACT
OBJECTIVES: The objectives of this research were to develop and evaluate a cell phone application based on the standard protocol for personal health devices and the standard information model for personal health records to support effective blood glucose management and standardized service for patients with diabetes. METHODS: An application was developed for Android 4.0.3. In addition, an IEEE 11073 Manager, Medical Device Encoding Rule, and Bluetooth Health Device Profile Connector were developed for standardized health communication with a glucometer, and a Continuity of Care Document (CCD) Composer and CCD Parser were developed for CCD document exchange. The developed application was evaluated by five healthcare professionals and 87 users through a questionnaire comprising the following variables: usage intention, effort expectancy, social influence, facilitating condition, perceived risk, and voluntariness. RESULTS: As a result of the evaluation of usability, it was confirmed that the developed application is useful for blood glucose self-monitoring by diabetic patients. In particular, the healthcare professionals stated their own views that the application is useful to observe the trends in blood glucose change through the automatic function which records a blood glucose level measured using Bluetooth function, and the function which checks accumulated records of blood glucose levels. Also, a result of the evaluation of usage intention was 3.52 +/- 0.42 out of 5 points. CONCLUSIONS: The application developed by our research team was confirmed by the verification of healthcare professionals that accurate feedback can be provided to healthcare professionals during the management of diabetic patients or education for glucose management.